Paper Info
Title
TV program segmentation using multi-modal information fusion
Abstract
A TV program segmentation algorithm is presented by the fusion of the multi-modal information in the large-scale videos. As "Inter-Programs" are generally inserted into the TV videos repeatedly, the macro structures of the videos can be effectively and automatically generated by identifying the video-audio features of the special sequences. The Electronic Program Guide (EPG) is used to organize the structures into the programs. Three sections are included in the algorithm, namely, the video-based non-supervised duplicate sequence detection, the audio-based special clip retrieval and the EPG-based 24-hour program segmentation. The algorithm has been tested in 60-day different-type TV videos. The F-measures of the multi-modal fusion and video-based duplicated sequence detection achieve the rates of over 98% and 96% respectively. These results show that the proposed method is highly efficient and effective for the TV Program segmentation.
Year
DOI
Venue
2011
10.1145/1991996.1992007
ICMR
Keywords
Field
DocType
special sequence,tv video,tv program segmentation algorithm,epg-based 24-hour program segmentation,60-day different-type tv video,multi-modal information,audio-based special clip retrieval,electronic program guide,multi-modal information fusion,tv program segmentation,multi-modal fusion,locality sensitive hashing,fusion
Electronic program guide,Locality-sensitive hashing,Computer vision,Pattern recognition,Segmentation,Computer science,Artificial intelligence,Macro,Information fusion,Modal
Conference
Citations 
PageRank 
References 
2
0.36
19
Authors
7
Name
Order
Citations
PageRank
Hongliang Bai115218.48
Lezi Wang2122.67
Gang Qin320.36
Jiwei Zhang4153.77
Kun Tao5615.37
Xiaofu Chang6121.99
Yuan DONG713925.66